An application of C2-Net atmospheric corrections for chlorophyll-a estimation in small reservoirs

Abstract

The use of remote sensing for land and water monitoring is not new, and satellite sensor images have been applied since the launch of the first NASA Landsat and Nimbus satellites (Baker and Smith, 1981)– (Shoaf and Lium, 1976). However, some datasets have proven to be applicable to different states and characteristics of specific water bodies, like oceans, which makes criteria difficult to extend to broader water mass types. Previous research has used remote sensing products along with algorithms and water quality indices, to assess the best monitoring practices. Other researchers have performed inland water bodies assessment using multiband indices, where band combinations address specific constituents. Some named indices are the Floating Algal Index, the Normalized Difference Chlorophyll Index (NDCI) (Mishra and Mishra, 2012), the Normalized Difference Suspended Sediment Index, and the Maximum Chlorophyll Index. Other indices specifically applied for Chl-a concentration include Two and Three Band Algorithms (2BDA and 3BDA) (Watanabe et al., 2018), Fluorescence Line Height (FLH) (Buma and Lee, 2020), (Zhao et al., 2010), and Surface Algal Bloom Index (Alawadi, 2010). These indices have been successfully used to identify algal blooms. During the last years, have focused on the evaluation of a wide variety of band combinations for the chlorophyll-a and turbidity determination. In (Zhan et al., 2022), forty band combinations were applied for the retrieval of chlorophyll-a concentration values, and twenty-four for the study of turbidity. It would be of great interest to test the methodologies considering both regional aspects and size and shape of reservoirs. In summary, the objective of the study is to test the applicability of Sentinel 2 images to monitor small reservoirs water quality in Extremadura.